Sex differences in the neural correlates underlying impairments in response inhibition and salience attribution in cocaine addiction

国家研究表明，过去十年中，妇女吸毒率有所上升， 美国的主要公共卫生问题。然而，女性在神经影像学中的代表性大大不足 研究，以及明确针对成瘾人群性别比较的研究的缺乏， 在研究药物成瘾的性别特异性神经生物学机制方面存在空白。在过去 十年来，在一系列磁共振成像（MRI）研究（在以前的支持下进行，包括 R01DA 023579，R01DA 020949），我们已经彻底绘制了可卡因成瘾的临床症状， 反应抑制和显著性归因（iRISA）的神经网络基础损伤。该模型 提出，药物以牺牲非药物相关的强化为代价， 与奖励处理的异常和抑制控制的伴随减少有关， 增加易感个体的成瘾严重程度（包括渴望，复发的代表）。iRISA模型 强调了多巴胺能神经支配的前额叶皮层（PFC）及其与中脑边缘系统的联系的作用。 和纹状体皮质下区域的功能和结构评估。然而，其中大部分 在患有可卡因使用障碍（iCUD）的男性个体中已经完成了神经成像研究。在 目前的项目，我们的目标是通过比较同等数量的男性和女性iCUD来扩大iRISA的覆盖范围; 为了测试该模型的普遍性（与药物特异性效应相比），我们还将包括使用阿片类药物的个体 疾病（iOUD）。我们将在奖赏加工、抑制控制和线索反应三个阶段进行功能性磁共振成像 任务，并在休眠状态期间检查任务相关激活之外的结果的可推广性。超出 功能激活和连接，解剖扫描将评估潜在的灰质完整性。 在所有目标中，健康对照将被纳入建立规范。我们假设女性iCUD与男性不同 从男性iCUD或女性对照中，以指示对iRISA的脆弱性增强的模式，包括 代偿性PFC激活和结构测量异常;将比较iCUD与iOUD 试探性的这一建议的新颖性进一步增强了探索性的目的，比较，在一个内部- 主题设计，月经周期（和荷尔蒙）的影响，并通过开发复杂的机器学习 算法，用于合并来自所有成像模态的数据，以产生自动组分类，以及 成瘾严重程度（包括渴望）预测工具。考虑到大多数关于成瘾的研究 发生在男性中，澄清iRISA神经基础的性别差异可以加强 研究两性的重要性，并建议不同的治疗策略可能对女性有效 （可能在月经周期的时间上影响最大），有助于开发量身定制的 （基于性别的）治疗选择。让男女人数相等将促进基础研究 并最终通过在未来的临床试验中最大限度地减少成本和不良反应来节省资源。

National studies show that drug use rates have increased in the last decade among women, comprising a major public health concern in the US. However, women are greatly underrepresented in neuroimaging studies, and the paucity of studies that explicitly target sex comparisons in addicted populations contributes to a gap in the study of the sex specific neurobiological mechanisms underlying drug addiction. Over the last decade, in a series of magnetic resonance imaging (MRI) studies (conducted with previous support including R01DA023579, R01DA020949), we have thoroughly mapped the clinical symptoms of cocaine addiction to the neural networks underlying impairments in Response Inhibition and Salience Attribution (iRISA). This model proposes that the drug assumes heightened salience at the expense of non-drug related reinforcement as associated with abnormalities in reward processing and concomitant decreases in inhibitory control, together increasing addiction severity (including craving, a proxy of relapse) in susceptible individuals. The iRISA model highlights the role of the dopaminergically innervated prefrontal cortex (PFC) and its connections to mesolimbic and striatal subcortical regions as assessed functionally and structurally. However, the majority of this neuroimaging research has been accomplished in male individuals with cocaine use disorders (iCUD). In the current project we aim to expand the reach of iRISA by comparing equal numbers of male to female iCUD; to test this model’s generalizability (vs. drug specificity effects), we will also include individuals with opioid use disorder (iOUD). We will conduct functional MRI during reward processing, inhibitory control and cue-reactivity tasks, and, to inspect generalizability of results beyond task-related activations, during resting-state. Beyond functional activations and connectivity, anatomical scans will assess the underlying gray matter integrity. Across all aims, healthy controls will be included to establish norms. We hypothesize female iCUD to differ from male iCUD, or female controls, in a pattern indicative of enhanced vulnerability to iRISA inclusive of compensatory PFC activations and abnormalities in structural measures; iCUD vs. iOUD comparisons will be exploratory. The novelty of this proposal is further enhanced by an exploratory aim to compare, in a within- subjects design, menstrual cycle (and hormonal) effects and by developing sophisticated machine-learning algorithms to incorporate data from all imaging modalities to yield an automated group classification and addiction severity (including craving) prediction tool. Considering that the majority of research in addiction occurs in males, clarification of the sex differences in the neural underpinnings of iRISA could reinforce the importance of studying both genders and suggest that different treatment strategies may be effective in women (potentially of most impact when timed vis-à-vis menstrual cycle), contributing to the development of tailored (gender-based) treatment options. Including equal numbers of women and men would advance basic studies of drug addiction and ultimately save resources by minimizing cost and adverse effects in future clinical trials.